Classification and Numbering of Dental Radiographs for an Automated Human Identification System
Abstract: Dental based human identification is commonly
used in forensic. In a case of large scale investigation, manual identification
needs a large amount of time. In this paper, we developed an automated human
identification system based on dental radiographs. The system developed has two
main stages. The first stage is to arrange a database consisting of labeled
dental radiographs. The second stage is the searching process in the database
in order to retrieve the identification result. Both stages use a number of
image processing techniques, classification methods, and a numbering system in
order to generate dental radiograph’s features and patterns. The first
technique is preprocessing which includes image enhancement and binarization,
single tooth extraction, and feature extraction. Next, we performed dental
classification process which aims to classify the extracted tooth into molar or
premolar using the binary support vector machine method. After that, a
numbering process is executed in accordance with molar and premolar pattern
obtained in the previous process. Our experiments using 16 dental radiographs
that consist of 6 bitewing radiographs and 10 panoramic radiographs, 119 teeth
objects in total, has shown good performance of classification. The accuracy
value of dental pattern classification and dental numbering system are 91.6 %
and 81.5% respectively.
Author: Anny Yuniarti,
Anindhita Sigit Nugroho, Bilqis Amaliah, Agus Zainal Arifin
Journal Code: jptkomputergg120034